Datamatics Technologies

About the Role

Key Responsibilities

1. Delivery Leadership (Project Execution)

• Lead end-to-end technical delivery of data platform implementation projects (e.g., data warehousing, data lakes, lakehouses, or modern BI platforms).
• Translate business requirements into technical specifications, architecture blueprints, and development tasks.
• Manage technical risks and dependencies; ensure projects are delivered on time, within scope, and with high quality.
• Collaborate with junior developers, data engineers, and cross-functional teams to drive execution.

2. Technical Governance & Quality Assurance

• Perform periodic technical health checks on in-progress projects to validate the technical approach, code quality, and architectural decisions.
• Identify areas of technical debt, performance bottlenecks, or scalability concerns and recommend actionable improvements.
• Establish and enforce best practices for data modeling, ETL/ELT pipelines, data governance, and security.
• Conduct peer reviews and technical audits to ensure consistency across multiple client engagements.

3. Pre-Sales & Solutioning Support

• Participate in technical discovery meetings with prospect customers to understand their data challenges, existing landscape, and success criteria.
• Design and present high-level solution architectures, technology recommendations, and effort estimates.
• Articulate the value proposition of proposed solutions clearly to both technical and non-technical stakeholders.
• Build proof-of-concepts (PoCs) or reference architectures to demonstrate technical feasibility during sales cycles.

4. Client & Stakeholder Communication

• Serve as a trusted technical advisor to client technical leads and architects.
• Facilitate workshops, sprint reviews, and technical status updates with clarity and confidence.
• Translate complex technical concepts (e.g., partitioning strategies, incremental loads, data lineage) into business-friendly language.

Required Qualifications

• 4–7 years of hands-on experience in data platform implementation (cloud or on-prem).
• Strong proficiency in SQL and at least one programming language (Python, Scala, or Java).
• Experience with cloud data platforms (Snowflake, BigQuery, Redshift, Synapse, or Databricks).
• Solid understanding of data modeling (Kimball, Inmon, Data Vault), ETL/ELT patterns, and workflow orchestration (Airflow, dbt, Azure Data Factory, or similar).
• Familiarity with data governance, cataloging, and quality tools (Collibra, Purview, Great Expectations, etc.) is a plus.

• Proven experience leading technical workstreams within Agile/Scrum or hybrid methodologies.
• Experience conducting technical reviews, audits, or readiness assessments on live projects.
• Ability to balance speed of delivery with long-term maintainability and performance.

• Excellent verbal and written communication skills – able to lead technical conversations with customers and internal stakeholders.
• Comfortable creating solution architecture diagrams, slide decks, and proposals for prospect meetings.
• Prior experience supporting pre-sales (estimations, solutioning, PoCs) is highly desirable.
• Strong problem-solving mindset with the ability to push back constructively when needed.

Nice to Have

• Cloud certification (AWS Solutions Architect, Azure Data Engineer, or GCP Data Engineer).
• Experience with modern data stack (dbt, Airbyte, Fivetran, Looker, Power BI).
• Background working in a consulting or services organization (client-facing delivery).